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Foundational understanding
Knows what AI tools are, what they do well and badly, and that outputs can be confidently wrong.
Workforce AI Readiness has two modules. Skills measures the practical competence to use AI effectively, safely, and within policy. Anxiety measures the trust, confidence, and psychological safety that decide whether capability becomes responsible use or quiet resistance. They are recommended together because skill without trust drives avoidance, and trust without skill drives unmanaged over-reliance. Either module also runs on its own.
Skills are assessed against five domains, segmented by role and AI exposure so that a developer, a recruiter, and a finance analyst are measured against the standards appropriate to each.
Knows what AI tools are, what they do well and badly, and that outputs can be confidently wrong.
Can frame a task, prompt productively, iterate, and integrate AI output into real work to a useful standard.
Verifies AI output, recognizes fabrication and bias, and knows when not to trust or use a result.
Knows what may and may not be entered into AI tools, which tools are sanctioned, and the policy boundaries that apply.
Applies AI to the specific, legitimate tasks of their function with judgment about where it adds value and where it does not.
The instrument is anonymous and framed supportively. The goal is honest signal, not surveillance. Results are segmented enough to be actionable but never so finely that individuals become identifiable.
The degree to which employees fear AI threatens their role, and whether that fear is being addressed or ignored.
Whether employees feel able to keep up, or feel exposed and behind, in the face of AI expectations.
Whether employees trust AI outputs appropriately, neither blind reliance nor blanket rejection.
Whether employees believe leadership is introducing AI fairly, transparently, and with their interests considered.
Whether employees feel safe raising concerns, admitting they do not understand a tool, or declining an unsafe AI use without penalty.
The cumulative strain of AI-driven change on top of other organizational change.
Anxiety results are read alongside the skills assessment. High anxiety paired with low competence signals a population that needs support before tools. High anxiety paired with high competence often signals a trust-in-organization problem rather than a capability one.
A scoping conversation about the segments you would assess, anonymity safeguards, and what running one or both modules would look like.